Electrical Signature Analysis to Quantify Human and Animal Performance on Fitness and Therapy Equipment such as a Treadmill

ABSTRACT

The invention is a human and animal performance data acquisition, analysis, and diagnostic system for fitness and therapy devices having an interface box removably disposed on incoming power wiring to a fitness and therapy device, at least one current transducer removably disposed on said interface box for sensing current signals to said fitness and therapy device, and a means for analyzing, displaying, and reporting said current signals to determine human and animal performance on said device using measurable parameters.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

This invention was made with United States Government support underContract No. DE-AC05-00OR22725 between the United States Department ofEnergy and U.T. Battelle, LLC. The United States Government has certainrights in this invention.

BACKGROUND OF THE INVENTION

Gait analysis usually involves the measurement and interpretation ofsequential events that occur in the gait cycle. The gait cycle includesall of the events occurring from one heel strike to the repeated heelstrike of the same foot. Essential gait measurement parameters includespace, time, and compressive forces. These measurements must beaccurate, reproducible and related in time to be of value. Additionalvalue results from real time data analysis to allow training for gaitstyle modification, or adjustments of gait devices like shoes or braces.

Various types and methods of gait analysis exist today ranging frommeasured distances and a stopwatch to computerized 3-D video gaitanalysis systems. The cost, utility and efficacy of each system maylimit their application in various settings. The Electrical SignatureAnalysis (ESA) system described herein provides a highly objective,comprehensive gait performance analysis.

BRIEF SUMMARY OF THE INVENTION

The invention is a human and animal performance data acquisition,analysis, and diagnostic system for fitness and therapy devices havingan interface box removably disposed on incoming power wiring to afitness and therapy device, at least one current transducer removablydisposed on said interface box for sensing current signals to saidfitness and therapy device, and a means for analyzing, displaying, andreporting said current signals to determine human and animal performanceon said device using measurable parameters.

One unique and valuable aspect of the ESA system is its simple anddirect ability to measure many of the fundamental characteristics ofgait patterns using a standard treadmill. ESA requires no restrictive orsophisticated instrumentation and poses no risk to subjects other thanwalking on the treadmill at comfortable speeds. The system has anexcellent market potential for demonstrating gait aberrations inrehabilitation settings, sports performance for coaches and athletes,and gait enhancements for footwear manufacturers.

ESA can be used to monitor physical condition and performance of humanand animals. ESA has long been used as a tool for monitoring thecondition and performance of pumps, valves and other electromechanicalmachinery, but has never been applied as a tool for analyzing human andanimal condition and quantifying performance.

To further investigate this concept, electric voltage and currentsignals were recorded from an AC-powered treadmill as a person walked onthe treadmill normally and in several irregular ways that simulatedvarious physical impairments. The variations in walking styles producedmany noticeable changes in the treadmill's electrical signatures, anddemonstrated this new approach for sensing and measuring variations inhuman and animal physical condition. These results can serve as afoundation for further development of ESA-based methods and ultimatelylead to the creation of new tools for measuring the physicalrehabilitation progress of people recovering from injuries and surgeriesthat alter flexibility, mobility, strength, and balance.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic of the general method of electrical signatureanalysis.

FIG. 2 is a photograph of the electrical interface box to a treadmillpower source.

FIG. 3 is a schematic of a treadmill embodiment having a simplifiedinterface box and a computer means for analyzing, displaying, andreporting the current signals.

FIG. 4 is a schematic of a treadmill embodiment having a simplifiedinterface box and an integrated treadmill means for analyzing,displaying, and reporting the current signals.

FIG. 5 is a schematic of the treadmill test setup.

FIG. 6 is a graphical output of the voltage (top) and current (bottom)signals while a person is walking on a treadmill.

FIG. 7 is a sample computer screen from the treadmill ESA software.

FIG. 8 is a graph showing the raw current waveform (top), full-waverectified waveform with peaks identified (middle), and stride profilewaveform constructed from rectified peaks (bottom).

FIG. 9 is a graph showing the average stride profile for a user walkingwith a normal gait.

FIG. 10 is a sample output of measurable parameters from the “A” (right)and “B” (left) stride profiles.

FIG. 11 is a graph showing the effect of added weight on an average leftstride profile.

FIG. 12 is a graph showing the effect of added weight on an averageright stride profile.

FIG. 13 is a graph showing the effect of a taped right ankle on theaverage stride profiles.

FIG. 14 is a graph showing the effect of an immobilized right leg on theaverage stride profiles.

DETAILED DESCRIPTION OF THE INVENTION

This invention is a device and method for detecting and monitoringphysical condition and performance of humans and animals. It exploitsthe treadmill's and other electromechanical device's electric motor as atransducer for sensing load variations caused by a person or animalwalking on the treadmill, and is a variation of Electrical SignatureAnalysis (ESA) technologies that were initially developed for assessingthe condition of electromechanical machinery.

Treadmill electric voltage and current signals were recorded as a personwalked on the treadmill normally and in several irregular ways thatsimulated various physical impairments. Using current and voltagemeasurements enables a calculation of power which can be used as anadditional analysis parameter. The variations in walking styles producedmany noticeable changes in the treadmill's electrical signatures, thusdemonstrating the sensitivity needed to perform human and animal gaitanalysis.

With further development, ESA-based instrumentation can be developed andcombined with conventional treadmills and other electrically-poweredhealth equipment to provide new inexpensive tools for monitoring andquantifying the physical rehabilitation progress of people recoveringfrom injuries and surgeries that have affected their gait, flexibility,mobility, strength, and balance. Other than clinical settings,applications of the invention include biomechanics sports conditioningand rehabilitation, direct results measurement for reporting progressand billing support to medical insurance companies, racehorse trainingand rehabilitation, athletic shoe and orthotic design, and prostheticresearch and design.

Gait analysis is essential in physical medicine and is a fundamentaltool of the orthopedist, physical therapist, and orthotist/prosthetist.The ability to assess and correct inefficient or dysfunctional gaitpatterns is fundamental to sound clinical practice. Gait aberrations canresult from pain, neurological disorders, and musculoskeletalimpairments and can lead to premature joint wear, myotendinous pain andfunctional disability. Long term, gait disorders may result in permanentdisability, loss of balance, loss of independence, and increased fallpotential.

ESA gives clinicians a new analysis tool that can be used independentlyor with other gait analysis techniques to increase accuracy andobjectivity of gait analysis. The physical therapist may use thistechnology to enhance gait efficiency and balance with a large varietyof cases in geriatric populations, post-fracture or post-surgical cases,injured athletes, and general sprains or strains. The orthotist may usethis technology to study the effects of various braces and orthoses. Theprosthetist could study gait efficiency and use this technology tomodify prosthesis to enhance the desired gait characteristics.

Beyond the realm of rehabilitation, ESA may prove to be very useful withanalysis of athletic performance, particularly with runners. One couldestablish characteristic ‘signatures’ of elite runners with the ESAprocess and compare them with other developing runners. The developingathlete can learn to model, and then feel the differences with moreefficient running motions using the ESA process. Coaches could use theprocess to train young runners and to analyze workouts in real time.

Athletic foot wear manufacturers may use the ESA process to study theeffect of various shoe modifications with running performance, motioncontrol for stability, and force attenuation. The ESA process couldprovide objective data for sport specific foot wear related to athleticperformance.

The ESA technology was originally invented and developed as a tool forassessing the condition of a wide variety of military, industrial, andconsumer electromechanical equipment. ESA can be used to detectequipment defects and degradation, and unwanted changes in processconditions. ESA is truly non-intrusive and does not interfere with theoperation of the equipment being monitored.

FIG. 1 illustrates the general ESA method. Load and speed variations inelectromechanical systems generally produce correlated variations incurrent and voltage. ESA analyzes these small perturbations and matchesthem to their source. The resulting time and frequency signaturesreflect loads, stresses, and wear throughout the system and provide thebasis for assessing the operational condition of the monitoredequipment.

Many machines and electrical appliances have been designed to directlyinteract with human and animals. The manner in which the human andanimal uses the appliance determines how hard the appliance must work,and how much electrical energy is required. For example, if a power sawis not used correctly, additional friction and binding can occur betweenthe saw blade and the material being cut. This results in the saw motorhaving to work harder; which causes it to draw more current. When usedcorrectly, the motor does not have to work as hard, and the electriccurrent is lower. Thus, by measuring the magnitude of the electriccurrent used by the saw, the manner in which the saw is being used isalso measured.

Other examples of machines whose operations are affected by how they areused include treadmills, exercise bikes, elliptical machines, and otherfitness equipment used in gyms and physical therapy centers. While thesemachines have been designed to promote physical fitness, their designsare inherently sensitive to the physical attributes, health, andabilities of the user. Like the saw example, it is believed that byobtaining the electrical signatures of these exercise devices as theyare being used, certain signature features will be present that areindicative of the physical condition and abilities of the user. Afteridentifying and correlating these features, they can be used to trackimprovement or degradation in the user's physical condition over time.

FIG. 3 is a schematic of a treadmill embodiment having a simplifiedinterface box and a computer means for analyzing, displaying, andreporting the current signals. The simplified interface box 39 includesa current transducer for obtaining current signals.

FIG. 4 is a schematic of a treadmill embodiment having a simplifiedinterface box and an integrated treadmill means for analyzing,displaying, and reporting the current signals. The simplified interfacebox 39 includes a current transducer for obtaining current signals andthe data is displayed on the treadmill stand itself. Other anticipatedembodiments include a fully integrated treadmill wherein all componentsof the invention are built into the treadmill.

In the test setup of FIG. 5, treadmill electrical signals were obtainedusing an electrical interface box 31 that was plugged into the treadmill30 and then into a 120 V wall outlet. The interface box 31 contains anexternal loop 32 for accessing the treadmill electric current using astandard clamp-on current transducer 33. The interface box 31 alsoprovides access to the full line voltage used by the treadmill 30. A20:1 splitter 34 was then used to reduce the voltage levels so that theycould be safely recorded on a data recorder 35. This interface box 31makes it possible to easily and safely acquire electrical signals fromany electrically powered exercise device such as a treadmill, anexercise bicycle, or an elliptical trainer.

FIG. 5 illustrates the general test setup. Electrical signals wereobtained with a digital data recorder 35 and subsequently analyzed usinga computer 36 and software that was specially developed for thisapplication. Treadmill data were acquired under a variety of conditions.Table 1 summarizes the test conditions and walking styles that wererecorded.

TABLE 1 Treadmill Treadmill Speed Incline Date (mph) (%) Walking StyleNov. 17, 2005 4 0 Normal walking Nov. 17, 2005 4 5 Normal walking Nov.17, 2005 4 10 Normal walking Nov. 22, 2005 3 0 Normal walking Nov. 22,2005 3 0 Walking, but with extended strides Nov. 22, 2005 3 0 Walkingnormal, but using the rails for support Nov. 22, 2005 3 0 Walking with ascissor gait Nov. 22, 2005 3 0 Walking with a sore toe Nov. 22, 2005 3 0Walking with a stiff knee Nov. 22, 2005 3 0 Walking normally, butpointing toes out Nov. 22, 2005 3 0 Walking on toes only Nov. 22, 2005 40 Normal walking Nov. 22, 2005 5 0 Normal walking Nov. 22, 2005 5 0Running Dec. 2, 2005 3 0 Normal walking with running shoes Dec. 2, 20053 0 Normal walking with no shoes Dec. 2, 2005 3 0 Normal walking withstreet shoes Dec. 2, 2005 3 0 Normal walking with taped ankle Dec. 2,2005 3 0 Normal walking with taped ankle and toes Dec. 2, 2005 3 0Normal walking with taped ankle and toes, and immobilized leg Dec. 2,2005 3 0 Normal walking with taped ankle and toes, and restricted(taped) knee Dec. 2, 2005 3 0 Normal walking with restricted (taped)knee only Dec. 2, 2005 3 0 Normal walking while carrying 30 lbs of extraweight

Treadmill voltage and current signals were recorded for all tests. Tominimize variables, the same treadmill was used for all tests, and thesame person served as the test subject for all tests. Several of thesetests are further described later.

The recorded voltage and current signals were initially played back andexamined using Adobe Audition, a commercially-available software packagedesigned to record, edit, and play audio signals. As shown in FIG. 6,walking on the treadmill produced very little impact on the magnitude ofthe voltage signals, but produced dramatic variations in the magnitudeof the electric current. For this reason, all additional analysisefforts focused on the current signals.

To analyze the electric current signals in more detail, a data analysis“virtual instrument” was developed using LabVIEW, a graphical dataacquisition and analysis platform. The software controls and displaysevolved as methods were identified to extract useful details(signatures) from the electric current data. Presently, the software isdesigned to apply a variety of ESA-based methods on treadmill electriccurrent data that has been saved in the popular Windows sound file (WAV)format.

FIG. 7 illustrates a sample screen from the software, and shows (in theupper left corner of the screen) various controls that provide theability to input the treadmill speed (in miles-per-hour) and a rangewithin which the users stride falls. For the example, the data shown istaken from a test when the treadmill was operating at 3.0 miles perhour. The stride range of the user is selected to be between 15 and 45inches.

The software provides a tool for converting the “raw” electric currentdata into a revealing stride profile by first full-wave rectifying thecurrent signal, and then using the rectified peaks to build the strideprofile waveform. FIG. 8 illustrates this process where the softwarebegins with “raw” data (top graph). After full-wave rectifying, theenvelope peaks are automatically identified (middle graph) and used toconstruct the stride profile (bottom graph). This example shows thenormal left-right stride signature of the user. The software thenperforms a frequency-analysis of the stride waveforms and calculates theoverall stride frequency (in steps per second). The individual stridewaveforms are then separated into two groups representing the left andright strides.

In order to identify which group is associated with which leg, the userconsistently stepped on the treadmill first using his right foot. Asthis ESA-based system is further developed, a more positive method ofidentifying right from left is needed. One method of accomplishing thisis to have the user wear a sensor on one leg that is preferably moresensitive only to one stride (e.g., their right) and transmit a signalto the data acquisition computer with each right step via a wirelesslink. The computer can then use this reference signal to positivelyidentify the right stride waveform data from the left. Instruments suchas foot switches are available which would positively identify left andright feet.

The load on the treadmill (and hence the current drawn by the treadmillsmotor) is sensitive to several factors, such as the weight of the user,the surface area of the belt that is in contact with the user, and thefrictional losses between the treadmill mechanical surfaces. Thesoftware calculates an average stride profile, based on analyzingnumerous stride waveforms and after accounting for the slightdifferences in the stride-to-stride durations in each leg. Thisaveraging process is intended to “average out” the effects of thetreadmill itself, since the user contacts a different section of thetreadmill belt with each step. The average stride profiles are thusbelieved to be predominantly influenced by the gait of the user, andthus provide a suitable and sensitive signature for performing gaitanalysis.

Typical average stride profiles are shown in FIG. 9 for the user walkingin a normal gait. As can be seen in the FIG. 9, differences existbetween the right and left stride profile of the user. For example, theaverage left stride is characterized by a larger overall magnitude (thusindicating a larger load to the treadmill) and is about 5 percent longerin duration than the average right stride. The specific causes for theprofile differences are not presently completely understood; however,they are repeatable and thus are believed to reflect user-specificconditions.

To better quantify the differences, the software also measures a varietyof parameters that are present in the stride profiles. These parametermeasurements are shown in FIGS. 10. Several of these parameters werejudged to be very sensitive indicators of gait anomalies such as strideprofile, average stride profile, average cycle fraction difference,stride length unbalance, estimated weight unbalance, difference in maxlocation, and difference in slope max location.

Average stride profiles are provided to illustrate the ability of ESAmethods to characterize gait variations. The following “abnormal”conditions are presented; normal walking with additional weight, normalwalking with taped right ankle, and taped right ankle and toes plusimmobilized right leg.

FIGS. 11 and 12 show the effect of the user carrying an additional 30lbs while walking on the treadmill. When carrying the additional weight,the magnitudes associated with the right stride increased an average of12.1 percent, and was relatively consistent throughout the entirestride. Similarly, the left side magnitudes increased an average of 11.0percent. Since both right and left strides were affected approximatelythe same, the “balance” between the right and left strides wasundisturbed.

A test was performed after taping the user's right ankle. This removedthe normal flexibility normally associated with the foot. When walkingwith a taped ankle, the balance between the two strides is significantlydisturbed and is dramatically seen in the average stride profiles shownin FIG. 13. The right profile duration is noticeable shortened, and itsmagnitudes during the majority of the stride are significantlydecreased. In contrast, the duration of the left profile increased,along with an increase in magnitudes throughout most of the stride.Thus, what is seen is a “spreading” of the two profiles as they move inopposite directions. This unbalance between the two strides isindicative of the differences in left and right strides, caused by therestricted movement of the right foot.

A test was performed with several concurrent restrictions: the user'sright toes and ankle were taped to prevent motion, and their right legwas immobilized by taping their knee. In this condition, the user walkedon the treadmill, thus producing the average stride profiles shown inFIG. 14. The addition of the taped toes and immobilized leg to thealready taped ankle further accentuated the unbalance between the twostrides, as shown by the increased spreading between the left and rightprofiles. In this extreme case, the user spent only 42 percent of thetime on their right foot, and 58 percent of the time on their left foot.The differences between the profile magnitudes were substantial. Onemethod of quantifying the profile magnitudes is by measuring the averageprofile magnitudes and subtracting the minimum magnitude. In thismanner, the average increase in treadmill running load associated witheach stride is measured.

For the immobile leg case, the average profile magnitude minus theprofile minimum for the compensating leg was 6525, which is almostdouble the magnitude of the right immobilized leg, which was 3344. Thismeasure, along with the change in stride duration, and other measurableparameters are all indicative of the severe unbalance between the twostrides, due to the imposed restrictions.

The average stride profiles that have been illustrated are only one wayof visualizing and quantifying the treadmills electrical signaturechanges resulting from a person walking on it. The profiles themselveshave many measurable characteristics that should correlate with knowngait patterns.

Initial treadmill ESA tests were performed using a test subject whowalked in various ways to simulate several foot and leg problems,including a “sore toe” and a “stiff knee.” The ‘sore-toe’ and ‘stiffknee’ gaits represent common clinical gait patterns seen inrehabilitation. The sore-toe or antalgic gait is often seen in caseswith pain problems related to the toes, foot or ankle. Examples mightinclude a sprained ankle, bunion, turf toe, osteoarthritis, fracture, orother foot injury. Gait aberrations would be seen throughout theweight-bearing phase of the gait cycle from heel strike, through early,mid and late stance, as well as toe-off. The characteristic pattern islimited compressive loading, apropulsive toe-off, reduced stance timeand reduced step and stride length on the affected side.

The ‘stiff knee’ gait would represent an individual who may have hadsurgery on the knee, wears a knee brace or immobilizer, hasosteoarthritis of the hip or knee, or is post fracture and in a cast forimmobilization. The characteristic gait abnormalities with the stiffknee are seen from mid-stance to toe-off and through the swing phase.These include reduced step and stride length, reduced swing time,circumduction of the hip to clear the foot, and limited toe-off andpropulsion. The immobile extremity would have to be carried forward,which increases loads on the hip and the low back.

Normal gait can be divided into a stance phase, which takes roughly 60%of cycle time, and a swing phase, which takes 40% of the cycle time.Different gait abnormalities affect these phases of the gait patterndifferently. The sore toe will want to minimize the time in compressiveloading to protect the injured foot, where the stiff knee must becarried forward rather than being propelled forward. The resulting gaitaberrations might reflect in the temporal, spatial and compressivemeasurements of the gait. The ESA process is sensitive to these gaitpatterns as well as being capable of identifying differences betweennormal left and right strides.

While there has been shown and described what are at present consideredthe preferred embodiments of the invention, it will be obvious to thoseskilled in the art that various changes and modifications can be madetherein without departing from the scope.

1. A human and animal performance data acquisition, analysis, anddiagnostic system for fitness and therapy devices comprising: aninterface box removably connected between a source of electrical powerand incoming power wiring to a fitness and therapy device, at least onecurrent transducer removably disposed on said interface box for sensingcurrent signals to said fitness and therapy device, and a means foranalyzing, displaying, and reporting said current signals to determinehuman and animal performance on said device using measurable parameters.2. The system of claim 1 wherein said fitness and therapy device is atleast one device selected from the group consisting of treadmill,exercise bike, and elliptical machine.
 3. The system of claim 6 whereinsaid at least one current transducer is a clamp-on type.
 4. The systemof claim 1 wherein said means for analyzing, displaying, and reportingfarther comprises fall-wave rectifying of said current signals.
 5. Thesystem of claim 1 wherein said measurable parameter is selected from thegroup consisting of stride profile, average stride profile, averagecycle fraction difference, stride length unbalance, estimated weightunbalance, difference in max location, and difference in slope maxlocation.
 6. A human and animal performance data acquisition, analysis,and diagnostic system for fitness and therapy devices comprising: aninterface box removably connected between a source of electrical powerand incoming power wiring to a fitness and therapy device, at least onecurrent transducer removably disposed on said interface box for sensingcurrent signals to said fitness and therapy device, at least one voltagetransducer removably disposed on said interface box for sensing voltagesignals to said fitness and therapy device, a data recorder forrecording said current signals and said voltage signals, and a computerhaving a means for analyzing, displaying, and reporting said currentsignals and said voltage signals to determine human and animalperformance on said device using measurable parameters.
 7. The system ofclaim 6 wherein said fitness and therapy device is at least one deviceselected from the group consisting of treadmill, exercise bike, andelliptical machine.
 8. The system of claim 6 wherein said at least onecurrent transducer is a clamp-on type.
 9. The system of claim 6 whereinsaid interface box further comprises an external loop.
 10. The system ofclaim 6 wherein said interface box further comprises a voltage splitter.11. The system of claim 6 wherein said means for analyzing, displaying,and reporting further comprises full-wave rectifying of said currentsignals and a power measurement.
 12. The system of claim 6 wherein saidmeasurable parameter is selected from the group consisting of strideprofile, average stride profile, average cycle fraction difference,stride length unbalance, estimated weight unbalance, difference in maxlocation, and difference in slope max location.
 13. A method ofdetermining human and animal performance on a fitness and therapy devicecomprising the steps of: coupling an interface box between a source ofelectrical power and incoming power wiring for a fitness and therapydevice, securing at least one current transducer to said interface boxfor sensing current signals to said fitness and therapy device, andconnecting a means for analyzing, displaying, and reporting said currentsignals to determine human and animal performance on said device usingmeasurable parameters.
 14. The method of claim 13 wherein said fitnessand therapy device is at least one device selected from the groupconsisting of treadmill, exercise bike, and elliptical machine.
 15. Thesystem of claim 6 wherein said at least one current transducer is aclamp-on type.
 16. The method of claim 13 wherein said means foranalyzing, displaying, and reporting further comprises full-waverectifying of said current signals.
 17. The method of claim 13 whereinsaid measurable parameter is selected from the group consisting ofstride profile, average stride profile, average cycle fractiondifference, stride length unbalance, estimated weight unbalance,difference in max location, and difference in slope max location.
 18. Amethod of determining human and animal performance on a fitness andtherapy device comprising the steps of: coupling an interface boxbetween a source of electrical power and incoming power wiring for afitness and therapy device, securing at least one current transducer tosaid interface box for sensing current signals to said fitness andtherapy device, securing at least one voltage transducer to saidinterface box for sensing voltage signals to said fitness and therapydevice, connecting a data recorder for recording said current signalsand said voltage signals, and connecting a computer having a means foranalyzing, displaying, and reporting said current signals and saidvoltage signals to determine human and animal performance on said deviceusing measurable parameters.
 19. The method of claim 18 wherein saidfitness and therapy device is at least one device selected from thegroup consisting of treadmill, exercise bike, and elliptical machine.20. The system of claim 6 wherein said at least one current transduceris a clamp-on type.
 21. The method of claim 18 wherein said interfacebox further comprises an external loop.
 22. The method of claim 18wherein said interface box further comprises a voltage splitter.
 23. Themethod of claim 18 wherein said means for analyzing, displaying, andreporting further comprises full-wave rectifying of said current signalsand a power measurement.
 24. The method of claim 18 wherein saidmeasurable parameter is selected from the group consisting of strideprofile, average stride profile, average cycle fraction difference,stride length unbalance, estimated weight unbalance, difference in maxlocation, and difference in slope max location. 25 The system of claim 1wherein the interface box is removably connected between a source ofelectrical power and incoming power wiring to a fitness and therapydevice by: an electrical power cable extending from a power outlet tothe interface box, and an electrical power cable extending from theinterface box to the fitness and therapy device.
 26. The system of claim6 wherein the interface box is removably connected between a source ofelectrical power and incoming power wiring to a fitness and therapydevice by: an electrical power cable extending from a power outlet tothe interface box, and an electrical power cable extending from theinterface box to the fitness and therapy device.
 27. A method ofanalyzing a physical condition of a subject human or animal, comprising:recording a waveform representing an electrical current supplied to afitness and therapy device; identifying a plurality of waveform peaks inthe recorded waveform; using the plurality of waveform peaks toconstruct a stride profile; determining a first average stride signatureand a second average stride signature that are representative of thesubject's physical condition based on the stride profile.
 28. The methodof claim 27 further comprising recording a full wave waveformrepresenting the electrical current supplied to the motor and rectifyingthe full wave waveform for identifying the plurality of waveform peaks.29. The method of claim 27 further comprising associating the firstaverage stride signature and the second average stride signature withright and left strides of the subject.
 30. The method of claim 27further comprising: performing a frequency analysis of at least one ofthe first average stride signature and the second average stridesignature; calculating at least one stride frequency in steps per unittime for the at least one of the first average stride signature and thesecond average stride signature.
 31. The method of claim 27 furthercomprising: performing a frequency analysis of the first average stridesignature and the second average stride signature; calculating a firststride frequency in steps per unit time for the first average stridesignature; calculating a second stride frequency in steps per unit timefor the second average stride signature; calculating an average stridefrequency difference between the first stride frequency and the secondstride frequency.